Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monit...Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monitoring and close-loop control applications. However, the PMUs data quality issue affects applications based on PMUs a lot. This paper proposes a simple yet effective method for recovering PMU data. To simply the issue, two different scenarios of PMUs data loss are first defined. Then a key combination of preferred selection strategies is introduced. And the missing data is recovered by the function of spline interpolation. This method has been tested by artificial data and field data obtained from on-site PMUs. The results demonstrate that the proposed method recovers the missing PMU data quickly and accurately. And it is much better than other methods when missing data are massive and continuous. This paper also presents the interesting direction for future work.展开更多
The method for constructing core collection ofMalus sieversii based on molecular marker data was proposed. According to 128 SSR allele of 109 M. sieversii, an allele preferred sampling strategy was used to construct M...The method for constructing core collection ofMalus sieversii based on molecular marker data was proposed. According to 128 SSR allele of 109 M. sieversii, an allele preferred sampling strategy was used to construct M. sieversii core collection, using the UPGMA （unweighted pair-group average method） cluster method according to Nei ＆ Li, SM, and Jaccard genetic distances, by stepwise clustering, and compared with the random sampling strategy. The number of lost allele and t-test of Nei＇s gene diversity and Shannon＇s information index were used to evaluate the representative core collections. The results showed that compared with the random sampling strategy, allele preferred sampling strategy could construct more representative core collections. SM, difference for construction of M. sieversii core collection. Jaccard, and Nei ＆ Li genetic distances had no significant SRAP （sequence-related amplified polymorphism） data and morphological data showed that allele preferred sampling strategy was a good sampling strategy for constructing core collection of M. sieversii. Allele preferred sampling strategy combined with SM, Jaccard, and Nei ＆ Li genetic distances using stepwise clustering was the suitable method for constructing M. sieversii core collection.展开更多
基金supported in part by National Natural Science Foundation of China(NSFC)(51627811,51707064)Project Supported by the National Key Research and Development Program of China(2017YFB090204)Project of State Grid Corporation of China(SGTYHT/16-JS-198)
文摘Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monitoring and close-loop control applications. However, the PMUs data quality issue affects applications based on PMUs a lot. This paper proposes a simple yet effective method for recovering PMU data. To simply the issue, two different scenarios of PMUs data loss are first defined. Then a key combination of preferred selection strategies is introduced. And the missing data is recovered by the function of spline interpolation. This method has been tested by artificial data and field data obtained from on-site PMUs. The results demonstrate that the proposed method recovers the missing PMU data quickly and accurately. And it is much better than other methods when missing data are massive and continuous. This paper also presents the interesting direction for future work.
基金financially supported by the National Natural Science Foundation of China (30871679)National 863 Program of China (2006AA100108)Agricultural Improved Variety Project of Shandong Province, China.
文摘The method for constructing core collection ofMalus sieversii based on molecular marker data was proposed. According to 128 SSR allele of 109 M. sieversii, an allele preferred sampling strategy was used to construct M. sieversii core collection, using the UPGMA （unweighted pair-group average method） cluster method according to Nei ＆ Li, SM, and Jaccard genetic distances, by stepwise clustering, and compared with the random sampling strategy. The number of lost allele and t-test of Nei＇s gene diversity and Shannon＇s information index were used to evaluate the representative core collections. The results showed that compared with the random sampling strategy, allele preferred sampling strategy could construct more representative core collections. SM, difference for construction of M. sieversii core collection. Jaccard, and Nei ＆ Li genetic distances had no significant SRAP （sequence-related amplified polymorphism） data and morphological data showed that allele preferred sampling strategy was a good sampling strategy for constructing core collection of M. sieversii. Allele preferred sampling strategy combined with SM, Jaccard, and Nei ＆ Li genetic distances using stepwise clustering was the suitable method for constructing M. sieversii core collection.
